dept. of ag & resource economics and centre for the study ... · member heterogeneity – can...
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Dept. of Ag & Resource Economics and Centre for the Study of Co-operativesUniversity of Saskatchewan
May 11, 2018
Keri Jacobs, Asst. Professor of Economics, Iowa State University
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Local co-operatives merging, acquiring assets from independents
Result is fewer co-ops over time, but not fewer locations
High-profile co-op mergers in Iowa (Landus), Nebraska (CVA), SD & ND (Agtegra)
Environment of concern about market power
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1980s: Financial troubles, no appreciable change in locations (private acquisitions), mirrored loss of farms during period
1990s: HTA contract debacle forced restructuring
Current: Recent uptick in activity, typically “mergers of equals”
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• Approx. 50 G&FS co-ops (aka mixed)
• a few single locations remain
• Largest (Landus, in black) has 70+ locations and annual revenues > $1b
Source: Iowa Institute for Cooperatives, May 2018
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DriversAccess to strategic assetsSuccession and retention, access to talented GMEnhanced operational efficiencyAccess to capitalMarket protection for producers
Nearing tolerance threshold?Members weary and wary
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Does firm performance improve post-merger?
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Profit margin = gross profit / sales
Return on sales = local profits / sales
Return on assets = local profits / fixed assets
Return on equity = local profits / total equity
Asset Turnover = sales / total assets
Operational expense efficiency = op exp / gross margins
Labor expense efficiency = local profits / personnel exp
Members’ share of total equity = allocated equity / total equity
Members’ share of local equity = allocated equity / local equity
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Should we care?
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Profit margin = gross profit / sales
Return on sales = local profits / sales
Return on assets = local profits / fixed assets
Return on equity = local profits / total equity
Asset Turnover = sales / total assets (-0.17 to -0.21)
Operational exp. eff. = op exp. / gross margins (-0.17 to - 0.27)
Labor exp. eff. = local profits / personnel exp. (0.19 – 0.26)
Members’ share of total equity = allocated / total equity
Members’ share of local equity = allocated / local equity (-0.17 to -0.21)
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Member heterogeneity – can you be ”the co-op” for all?
Member perceptions of value proposition – the great balancing and education act
Co-ops who hang the value of consolidation on efficiency and performance have a post-merger problem
Board culture and membership culture
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Early joint work with Drs. Georgeanne Artz and Wendong Zhang, Iowa State University
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Observed consolidation in the grain marketing industry – all levels of the supply chain Fewer marketing firms, but not necessarily fewer grain-buying
locations
“Co-ops are getting too big.”
“There’s less competition for grain.”
What, if at anything, has been the impact of consolidation on grain bids to producers? Is there evidence of market power?
Are co-op and independent bids systematically different?
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Co-op consolidation data since 1979 Can observe locations’ ownership over time “Markets” with more/less concentration of grain buyers
Geograin Data Weekly corn and soybean bids from grain receiving locations
in Iowa (co-ops and independents): June 1998 – Nov 2014 Price bids include basis and contract price 393 markets in Iowa “Market” factors, i.e., rail and river loading, processor, feed mill
Currently match 264 of our 540 co-op locations to Geograinbid data
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Interesting questions related to consolidation
Spatially: across markets, do we identify differences in bids that are related to the degree of firm-level competition for grain? (monopsonistic spatial pricing evidence) Do markets where co-ops compete with independents have ‘better
bids’ than markets without co-ops? Do markets where co-ops compete with other co-ops have
better/worse bids than?
Temporally: within markets, do we identify differences in bids that are related to firm size, co-op consolidations and acquisitions? Do relative bids change over time as a result of co-op
consolidations and acquisitions?
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Simple model: 𝑎𝑎𝑎𝑎𝑎𝑎 𝑚𝑚𝑚𝑚𝑚𝑚𝑚𝑚𝑚𝑚𝑚𝑚𝑚 𝑏𝑏𝑏𝑏𝑏𝑏𝑖𝑖,𝑡𝑡 = 𝛼𝛼 + 𝑋𝑋𝑖𝑖,𝑡𝑡′ 𝛽𝛽 + 𝜇𝜇𝑖𝑖 + 𝑎𝑎𝑖𝑖,𝑡𝑡 RE model with monthly dummies, weekly price data
Results from the model using 2002 data that include ‘competition’ in a certain radius and firm size are anomalous
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Simple model: 𝑎𝑎𝑎𝑎𝑎𝑎 𝑚𝑚𝑚𝑚𝑚𝑚𝑚𝑚𝑚𝑚𝑚𝑚𝑚 𝑏𝑏𝑏𝑏𝑏𝑏𝑖𝑖,𝑡𝑡 = 𝛼𝛼 + 𝑋𝑋𝑖𝑖,𝑡𝑡′ 𝛽𝛽 + 𝜇𝜇𝑖𝑖 + 𝑎𝑎𝑖𝑖,𝑡𝑡When ‘firm size’ and competition indicator variables are
dropped, the results using 1999 – 2014 data make more sense
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Why do cooperatives offer significantly lower corn and soybean prices? How does this inform the impacts of consolidation on producers?Competition in a local area seems to be generating
lower commodity prices, not higher. What are we missing or not controlling for? Is there a reason to think that this type of study
cannot be used to answer the market power question?How much can we expect to gain from a more
sophisticated (spatial) analysis?
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KERI L. [email protected]